Hi All,
I am using the cppls function in the pls package, and I want to use cross
validation to determine the best number of components. Since Hastie et al
recommended a "one standard error rule", i.e., choose the most parsimonious
model whose error is no more than one standard error above
the error of the best model, I am wondering how I can get the standard
error of misclassification rate from pls package?
Thank you,
Cindy
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